Introduction to Bayesian Analysis in Python-P2P
Bayesian statistics is an effective tool for solving some inference problems when the available sample is too small for more complex statistical analysis to be applied. This course teaches the main concepts of Bayesian data analysis. It focuses on how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, model checking, and validation.
The course introduces the framework of Bayesian Analysis. Complex mathematical theory will be sidestepped in favor of a more pragmatic approach, featuring computational methods implemented in the Python library PyMC3. We present several instances of analysis scenarios.

Introduction to Bayesian Analysis in Python-P2P
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 10M | 231 MB
Genre: eLearning | Language: English
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